A general perspective is provided on both on hypothesis testing and discriminative analyses, by which matrix-variate discriminative analyses are proposed based on the matrix normal distribution, featured by a bi-linear extension of Fisher linear discriminant analysis and a further extension to binary variables. Moreover, a general formulation is proposed for integrative hypothesis testing and f...

rapid exploratory field survey, to identify indigenous chicken ecotypes was conducted in north gondar zone of ethiopia. chicken ecotypes including necked neck, gasgie and gugut from quara, alefa and tache armacheho districts were identified, respectively. morphological variations among the three study populations and nine measurable traits were evaluated. general linear model, canonical discrim...

when the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. in this paper, we propose a supervised feature extraction method based on discriminant analysis (da) which uses the first principal component (pc1) to weight the scatter matrices. the proposed method, called da-pc1, copes with the small sample size problem and has...

We consider a semiparametric generalisation of normal-theory discriminant analysis. The semiparametric model assumes that, after unspecified univariate monotone transformations, the class distributions are multivariate normal. We introduce an estimation procedure based on the distribution quantiles, in which the parameters of the semiparametric model are estimated directly without estimating th...

Image set based classification (ISC) has attracted lots of research interest in recent years. Several ISC methods have been developed, and dictionary learning technique based methods obtain state-ofthe-art performance. However, existing ISC methods usually transform the image sample of a set into a vector for processing, which breaks the inherent spatial structure of image sample and the set. I...